• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.183-189
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• 2023

A stroke is a medical disease where a blood vessel in the brain ruptures, causes damage to the brain. If the flow of blood and different nutrients to the brain is intermittent, symptoms may occur. Stroke is other reason for loss of life and widespread disorder. The prevalence of stroke is high in growing countries, with ischemic stroke being the high usual category. Many of the forewarning signs of stroke can be recognized the seriousness of a stroke can be reduced. Most of the earlier stroke detections and prediction models uses image examination tools like CT (Computed Tomography) scan or MRI (Magnetic Resonance Imaging) which are costly and difficult to use for actual-time recognition. Machine learning (ML) is a part of artificial intelligence (AI) that makes software applications to gain the exact accuracy to predict the end results not having to be directly involved to get the work done. In recent times ML algorithms have gained lot of attention due to their accurate results in medical fields. Hence in this work, Stroke disease identification system by using Machine Learning algorithm is presented. The ML algorithm used in this work is Artificial Neural Network (ANN). The result analysis of presented ML algorithm is compared with different ML algorithms. The performance of the presented approach is compared to find the better algorithm for stroke identification.

• 한국구조물진단유지관리공학회 논문집
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• 제23권7호
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• pp.87-94
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• 2019

최근 구조물 계측분야에서 구조물의 동적 변위응답 측정에 관한 연구가 주목을 받고 있다. 본 연구는 이와 같은 동적 변위데이터의 활용도를 넓히고자 구조안전도 평가를 위한 방법론 제시를 목표로, 동적 변위데이터를 활용하여 부공간 시스템 식별법이 적용된 구조물 물리량 추정기법을 개발하였다. 진동 변위 데이터로부터의 상태공간모델을 추정하기 위한 부공간 시스템 식별 이론과 시스템의 물리량을 도출하기 위한 물리해석 기법을 제시하였고 실험적 검증을 위해 동적 실험을 수행하였다. 3자유도 철골 구조물을 제작하여 진동대를 활용해 지반 가진하여 각 층의 변위 데이터와 진동대의 가속도 데이터를 계측하였다. 계측된 데이터를 활용해 이산화 된 상태공간모델을 생성하였고 정밀도 파악을 위해 상태공간방정식을 통한 전산 해석을 수행하였으며, 철제 구조물의 상태공간모델로부터 층강성을 추출하였다. 또한 상태공간모델로부터 추출된 층강성을 기준으로 5가지의 기둥강성 보강 및 손상 시나리오를 설정하여 매 시나리오별 층강성 변화율을 추출하였으며 동일한 조건의 보강 및 손상의 경우, 강성 변화가 높은 일치율을 보이는 것을 확인하였다.

• Smart Structures and Systems
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• 제26권3호
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• 융합보안논문지
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• 제22권5호
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• pp.11-20
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• 2022

인터넷과 웹 기술이 모바일 장치 중심으로 발전하면서 이미지 데이터는 사람, 텍스트, 공간 등 다양한 유형의 민감정보를 담고 있다. 이러한 특성과 더불어 SNS 사용이 증가하면서 온라인 상의 개인정보가 노출되고 악용되는 피해 규모가 커지고 있다. 그러나 개인정보보호를 위한 다중 유형 객체 탐지 기반의 비식별화 기술에 관한 연구는 미흡한 상황이다. 이에 본 논문은 기존의 단일 유형 객체 탐지 모델을 병렬적으로 이용하여 다중 유형의 객체를 탐지 및 비식별화하는 인공지능 모델을 제안한다. Cutmix 기법을 통해 사람과 텍스트 객체가 함께 존재하는 이미지를 생성하여 학습 데이터로 구성하고, 사람과 텍스트라는 다른 특징을 가진 객체에 대한 탐지 및 비식별화를 수행하였다. 제안하는 모델은 두 가지 객체가 동시에 존재할 때 0.724의 precision과 0.745의 mAP@.5 를 달성한다. 또한, 비식별화 수행 후 전체 객체에 대해 mAP@.5 가 0.224로, 0.4 이상의 감소폭을 보였다.

• Structural Engineering and Mechanics
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• 제7권4호
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• pp.387-400
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• 1999

Damage detection in civil engineering structures using the change in dynamic system parameters has gained a lot of scientific interest during the last decade. By repeating a dynamic test on a structure after a certain time of use, the change in modal parameters can be used to quantify and qualify damages. To be able to use the modal parameters confidentially for damage evaluation, the effect of other parameters such as excitation type, ambient conditions,... should be considered. In this paper, the influence of excitation type on the dynamic system parameters of a highway prestressed concrete bridge is investigated. The bridge, B13, lies between the villages Vilvoorde and Melsbroek and crosses the highway E19 between Brussels and Antwerpen in Belgium. A drop weight and ambient vibration are used to excite the bridge and the response at selected points is recorded. A finite element model is constructed to support and verify the dynamic measurements. It is found that the difference between the natural frequencies measured using impact weight and ambient vibration is in general less than 1%.

• 한국구조물진단유지관리공학회 논문집
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• 제9권4호
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• pp.195-201
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• 2005

본 논문에서는 확장 사영필터를 적용하여 구조물의 손상추정법을 제안하였다. 필터이론은 지금까지 역문제 해석에서 많은 관심을 받아왔고 또한 다양한 문제에 적용되어 그 유효성을 보여 왔다. 본 논문에서는 사영필터를 이용한 손상추정 역해석법 알고리즘을 제시하였고 제안 해법의 유효성을 보이기 위하여 트러스 구조의 자유진동문제를 대상으로 하여 해석 예를 보였다.

• Steel and Composite Structures
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• 제22권1호
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• pp.13-24
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• 2016

In the present paper, glass fibers are substituted partially with monofilament fishnet and polyester matrix for making the composites. The composite specimens were prepared in accordance with ASTM for analyzing the flexural strength and dynamic mechanical properties. Furthermore, machinability revealed the interaction of glass fiber and partial substituted monofilament fishnet fiber with the matrix. Fiber pullouts on the fractured specimen during the physical testing of the composites are also investigated by COSLAB microscope. The results reveal that the fishnet based composites have appreciably higher flexural properties. Furthermore, the glass fiber, woven roving and fishnet composite has more storage modulus and significant mechanical damping. The composite specimens were fabricated by hand lay-up method. Hence, these composites are the possible applications to develop the value added products. The results of this study are presented.

• Journal of Mechanical Science and Technology
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• 제17권5호
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• pp.637-646
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• 2003

In the previous study, the inverse perturbation method was used to identify structural damages. Because all unmeasured DOFs were considered as unknown variables, considerable computational effort was required to obtain reliable results. Thus, in the present study, a system condensation method is used to transform the unmeasured DOFs into the measured DOFs, which eliminates the remaining unmeasured DOFs to improve computational efficiency. However, there may still arise a numerically ill-conditioned problem, if the system condensation is not adequate for numerical Programming or if the system condensation is not recalibrated with respect to the structural changes. This numerical problem is resolved in the present study by adopting more accurate accelerated improved reduced system (AIRS) as well as by updating the transformation matrix at every step. The criterion on the required accuracy of the condensation method is also proposed. Finally, numerical verification results of the present accelerated inverse perturbation method (AIPM) are presented.

• Smart Structures and Systems
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• 제5권4호
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• 전산구조공학
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• 제11권3호
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• pp.199-212
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• 1998

본 연구에서는 기설구조물에 대한 손상도 추정기법과 내진능력평가 방법에 대하여 연구하였다. 구조물의 손상도를 추정하는 방법으로는 소수의 계측 데이터를 이용한 모드섭동법(inverse modal perturbation)을 이용하였다. 구조물의 손상은 강성행렬의 감소로 표현하여, 각 요소행렬에 대한 손상을 손상지수를 사용하여 나타내었다. 구조적 손상과 이에 기인한 고유진동 특성의 변화량과의 관계를 섭동방정식으로부터 구한 후, 이로부터 손상지수와 고유진동 특성의 변화량과의 관계를 유동하였다. 따라서 손상 전과 후에서 구조물의 고유진동수와 모드형상을 측정하여 섭동식의 해를 구함으로써 구조물의 강성행렬의 감소로 나타나는 구조물의 손상도를 추정하게 된다. 손상도 추정에 의해 평가된 강성의 변화량에 기인한 손상 후의 기설구조물의 지진응답, 내진능력과 지진손상도의 평가를 손상전과 비교하였다. 내진능력은 구조부재에서 회전연성도 능력의 경험식을 이용하여 평가하였고, 지진손상도의 평가는 가장 많이 사용되는 방법인 Park & Ang 방법을 사용하였다. 예제해석은 다른 지진하중을 받는 2층과 8층의 예제구조물에 대해서 수행하였다.